CSIG-01. DEFINING THE INVOLVEMENT OF THE PERIVASCULAR NICHE IN BRAIN TUMOR METASTASES
Bibliographic record
Abstract
Abstract Medulloblastomas (MB) are the most prevalent malignant pediatric brain tumors, originating in either the cerebellum or the dorsal brainstem. They are classified into four distinct subgroups (WNT, SHH, Group 3, and Group 4), characterized by unique gene expression profiles, metastatic patterns, and recurrence rates. Metastatic progression of MB is frequently associated with poor prognosis, affecting approximately 30% of patients at diagnosis. Despite considerable research on primary tumors, there are currently no approved specific treatments for MB leptomeningeal metastases. Thus, gaining further insights into metastatic MB and developing targeted therapies are imperative. The leptomeningeal niche, where metastatic MB tumor cells reside, comprises a complex network of blood vessels supported by perivascular cells, including pericytes, smooth muscle cells, and fibroblasts. However, the specific adhesion molecules and signaling pathways within the leptomeningeal niche that contribute to tumor cell colonization remain elusive. In this study, we hypothesize that the perivascular niche plays a critical role in the colonization and survival of metastatic cells within the leptomeninges. To investigate this, we employed an innovative sLP-mCherry niche labeling system in conjunction with single-cell RNA sequencing to spatially identify and examine the perivascular cells neighboring metastatic MB tumor cells. Through our analysis, we identified upregulated genes associated with cholesterol export in tumor-associated perivascular cells, suggesting their potential involvement in supporting metastatic cell colonization. To further explore this mechanism, we utilized CRISPR and lentiviral overexpression constructs to modulate cholesterol uptake in MB cell lines, observing subsequent changes in metastatic burden. In summary, our study elucidates the importance of the perivascular niche in metastatic medulloblastomas and provides novel insights into the molecular mechanisms that drive tumor cell colonization within the leptomeninges. These investigations into the lipid transport mechanism in the vascular microenvironment opens doors for the development of innovative treatments targeting MB metastases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".